基于改进多模型FDA的间歇生产过程的故障诊断

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基于改进多模型FDA的间歇生产过程的故障诊断

蒋丽英^a,b;谢磊^a; 王树青^a

^aNational Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China
^b Shenyang Institute of Aeronautical Engineering, Shenyang 110034, China

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2006-06-28 发布日期:2006-06-28
通讯作者: 蒋丽英

Fault Diagnosis for Batch Processes by Improved Multi-model Fisher Discriminant Analysis

JIANGLiying^a,b;XIELei^a; WANGShuqing^a

a National Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China
b Shenyang Institute of Aeronautical Engineering, Shenyang 110034, China

Received:1900-01-01 Revised:1900-01-01 Online:2006-06-28 Published:2006-06-28
Contact: JIANG Liying

摘要/Abstract

摘要： Since there are not enough fault data in historical data sets, it is very difficult to diagnose faults for batch processes. In addition, a complete batch trajectory can be obtained till the end of its operation. In order to overcome the need for estimated or filled up future unmeasured values in the online fault diagnosis, sufficiently utilize the finite information of faults, and enhance the diagnostic performance, an improved multi-model Fisher discriminant analysis is represented. The trait of the proposed method is that the training data sets are made of the current measured information and the past major discriminant information, and not only the current information or the whole batch data. An industrial typical multi-stage streptomycin fermentation process is used to test the per-formance of fault diagnosis of the proposed method.

关键词: fault diagnosis;Fisher discriminant analysis;batch processes

Abstract: Since there are not enough fault data in historical data sets, it is very difficult to diagnose faults for batch processes. In addition, a complete batch trajectory can be obtained till the end of its operation. In order to overcome the need for estimated or filled up future unmeasured values in the online fault diagnosis, sufficiently utilize the finite information of faults, and enhance the diagnostic performance, an improved multi-model Fisher discriminant analysis is represented. The trait of the proposed method is that the training data sets are made of the current measured information and the past major discriminant information, and not only the current information or the whole batch data. An industrial typical multi-stage streptomycin fermentation process is used to test the per-formance of fault diagnosis of the proposed method.

Key words: fault diagnosis, Fisher discriminant analysis, batch processes

蒋丽英,谢磊, 王树青. 基于改进多模型FDA的间歇生产过程的故障诊断[J]. CIESC Journal.

JIANGLiying,XIELei, WANGShuqing. Fault Diagnosis for Batch Processes by Improved Multi-model Fisher Discriminant Analysis[J]. .

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基于改进多模型FDA的间歇生产过程的故障诊断

Fault Diagnosis for Batch Processes by Improved Multi-model Fisher Discriminant Analysis

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